Embodiments of this disclosure will describe devices and methods for conducting measurements to determine status and/or health of tissue. One area of the disclosure will address neuromuscular diseases, which are very common. In 2009, there were over 18 million outpatient physician encounters with patients diagnosed with a range of neuromuscular diseases, from ALS to myoneural disorders like myasthenia gravis. These episodes generated nearly $7B in physician charges and can only be expected to grow as the episode volume is expected to reach over 20 million by 2014 (+8.25%).
Another area our disclosure will address common medical complaints, such as, e.g., lower back and neck pain. These common medical complaints are sometimes the primary causes of disability, lost productivity, and medical costs. For example, 60-80% of adults experience at least one significant episode of back pain in their lifetime. In a single year, about 15% will have debilitating back pain, and a substantial proportion will seek medical attention. Lower back pain has been estimated as the fifth or higher leading cause of all medical visits, and the first or second leading cause for patients seeking evaluation and treatment of a condition. Stated another way, about 4-5% of all medical encounters are related to back pain. In two major health surveys (National Health Interview Survey and National Health and Nutrition Survey), from 2004-2008, 28-40% of the U.S. population experienced neck or back pain in a three-month period, with 14-21% experiencing neck pain. Of the total group, 26-33% experienced associated radicular pain in a limb. Remarkably, lumbosacral and cervical pain together caused 5% of all U.S. health care visits in the in 2006.
Costs associated with care of individuals with low back and neck pain are huge. For example, in 2006, 44.4 million patients sought medical attention for low back pain, which was the chief complaint in 45.1 million encounters; an additional 13.2 million medical encounters were for neck pain. Annual cost of back pain in the US is $20-50 billion. Direct medical costs in 2002-2004 for spine problems were $193.9 billion, with $30.3 billion attributed specifically to spine pain. Indirect costs of lost wages are estimated at $14 billion annually, and in 2008, 385 million work days were lost due to back pain. The subgroup of patients with pain radiating to the limb, as occurs with disc herniation or spinal stenosis, had the highest numbers of bedridden and lost work days. Non-physician health care visits, e.g., physical therapy and other services, numbered 173.5 million from 2002-2004.2 Utilization is increasing, with ambulatory physician visits up 2.5% and non-physician visits up 10.2% from 1996-1998 to 2002-2004, with total increase in health care costs for spine of 24.5% (mean) and 48.9% (aggregate) in the same time period.
Another area our disclosure will address is the muscular health of older adults, which is the fastest growing segment of the population. Health care cost are exceptionally high for older adults with declining function, accounting for a disproportionate fraction of national health care expenditures. Muscle weakness is an independent risk factor for disability and mortality among older adults. Age associated loss of muscle mass, known as sarcopenia, is an important factor identified as relevant to mortality and disability.
In a recent and important editorial on sarcopenia and muscle function, Ferrucci et. al. (L. Ferrucci, R. de Cabo, N. D. Knuth, S. Studenski “Of Greek heroes, wiggling worms, mighty mice and old body builders”, J. Gerontol A Biol Sci Med Sci 2012; 67:13-6, [Ferrucci 2012] which is incorporated herein in its entirety by reference) advocated for a clinical approach in evaluating age associated muscle impairments, stating that after an initial mobility assessment to stratify patient risk for adverse outcomes (e.g., disability and mortality), muscle strength should be measured and a decision tree assessment used to evaluate muscle quality and function.
Both the general research community and the U.S. Food and Drug Administration (FDA) recognize the importance of improved biomarkers for neuromuscular disease research to assist with early diagnosis and track disease progression over time and response to therapy. Even more fundamentally, the concept of biomarker has expanded beyond its earlier definition that was restricted to molecular indices and now includes, but it not limited to, imaging and other methodologies. In fact, the FDA defines a biomarker as any objective test of disease status that cannot be influenced by the state of mind of the patient or examiner. The FDA recently developed biomarker definitions including diagnostic biomarkers for disease identification, response predictive biomarkers for assessing subgroups of individuals more likely to respond to a specific therapy, and prognostic biomarkers, for evaluating likelihood of disease onset or progression without any form of intervention. The FDA definitions provided herein are for discussions and references purposes only, and are not intended to limit any term contained herein. Two categories of biomarkers include response identification biomarkers (also called pharmacodynamic biomarkers) and biomarkers as surrogate endpoints in clinical trials. As a result, the FDA is revamping its approach to drug approval based on such surrogate endpoints. Previously, approval demanded evidence of change in a clinical outcome measure, such as, e.g., improved physical function or activity. In the future, however, it may be possible for a biomarker, which is established as a surrogate endpoint in a clinical trial, to obtain “qualification” status through the FDA as a surrogate endpoint, helping speed study and approval of effective therapies.
One technique for evaluating muscles is intramuscular electromyography (EMG.) EMG includes, but is not limited to, a technique for evaluating and recording the electrical activity produced by muscles, including, e.g., skeletal muscles. EMG may be performed using an instrument called an electromyograph, to produce a record called an electromyogram. An electromyograph may detect, among other things, the electrical potential generated by muscle cells when the cells are electrically or neurologically activated. The detected signals may be analyzed to detect, among other things, medical abnormalities, activation level, recruitment order or to analyze the biomechanics of human or animal movement. EMG is exceedingly intrusive in that it uses the insertion of needles through the skin and into the muscles and the use of these needles to measure electrical potential.
Electrical impedance myography (EIM) is a novel technological approach to effectively address these limitations. Unlike standard electrophysiological approaches, EIM is less directly dependent upon inherent electrical potential of muscle or nerve tissue. EIM is based on electrical bioimpedance. It measures the effect of tissue structure and properties on flow of extremely small, non-intrusive amounts of electrical current. Unlike standard bioimpedance approaches, however, measurements can be performed over small areas of muscle and incorporate sophisticated analytic tools. In EIM, electrical current, such as, e.g., high-frequency alternating current, may be applied to localized areas of muscle via electrodes (e.g., surface electrodes) and the consequent surface voltage patterns may be analyzed. Although data can be obtained with off-the-shelf bioimpedance devices, these devices are far from ideal in terms of providing useful data reliably, as discussed in more detail below.
FIG. 62A illustrates the concepts underlying EIM. Electrical current (sinusoid “a”) is applied via two or more outer surface electrodes generating a voltage difference measured by the two or more inner electrodes (sinusoid “b”). The voltage may be proportional to tissue resistance (R). Myocyte membrane lipid bilayers are capacitive in nature (e.g., they briefly store and then release some or all of the stored charge) and so exhibit reactance (X), making the voltage sine wave out of phase with applied current wave. Reactance and resistance values may be combined to obtain the summary phase angle (θ) via the relationship θ=arctan(X/R). FIG. 62B shows changes seen in diseased or less than ideal muscle tissue. Here, presence of connective tissue, fat and reduced muscle mass, among other things, may increase measured resistance; muscle fiber atrophy and loss also results in reduced reactance (e.g., timing of voltage sinusoid is now only slightly shifted relative to current). Thus, phase angle, as well as the resistance and reactance may be used to measure, e.g., disease progression. As disease advances, reactance and phase angle may decrease whereas resistance may increase.
Two additional aspects to EIM may include:                a) strong frequency dependence of EIM data. Thus, performing EIM measurements across a range of frequencies may help to characterize tissue. FIG. 63 shows multifrequency data “d” from a normal subject and from a patient with advanced ALS (Emory U. stem cell study), which is denoted by “e”. Note major alteration in impedance parameters across the frequency spectrum.        b) electrical anisotropy—directional dependence of current flow. Typically, electrical current flows relatively easily along muscle fibers than across them conferring a readily detectable anisotropy. Alteration in electrical anisotropy can also be used as a measure to evaluate muscle tissue to, e.g., determine a disease state, and early data show that anisotropy increases in, among other things, ALS.        
Although much previous EIM work was done with off-the-shelf whole-body bioimpedance systems, for example, using these systems for localized impedance measurements may be problematic for a variety of reasons, including, but not limited to, the systems: 1) may not be calibrated for the very different impedances found in localized areas of tissue, such as, e.g., muscle tissue; 2) may be unable to effectively measure and account for muscle anisotropy; 3) rely on multiple, clumsy adhesive electrodes that may be slow to apply and result in spacing variability; and 4) may operate over a limited frequency range that may miss certain clinical information. Thus, there is a need for a handheld, rapidly applied, broadly capable, robust EIM system for bedside use.
There are some reports of the use of electrical impedance for biometric purposes. Examples of such uses may be found in: U.S. Pat. No. 6,122,544 to L. W. Orgon “Electrical Impedance Method and Apparatus for Detecting and Diagnosing Diseases” (Orgon 544); U.S. Pat. No. 6,768,921 to Leslie W. Organ, K. C. Smith, Reza Safaee-Rad, M. Graovac, G. P. Darmos, and I. Gavrilov, “Electrical impedance method and apparatus for detecting and diagnosing diseases” (Organ 921); U.S. Pat. No. 6,845,264 and PCT Application Publication No. WO 00/19894, Skladnev; Victor, Thompson; Richard L., Bath; Andrew R., “Apparatus for recognizing tissue types”, (Skladnev 264); U.S. Pat. No. 6,723,049 and Australian Application No. PRS718, Skladnev; Victor Nickolaevich, Blunsden; Christopher Kingsley, Stella; Rita “Apparatus for tissue type recognition using multiple measurement techniques” (Skladev 049); U.S. Pat. No. 7,212,852 to K. C. Smith, J. S. Ironstone, F. Zhang, “Bioimpedance measurement using controller-switched current injection and multiplexer selected electrode connection”, (Smith 852); U.S. Pat. No. 7,457,660 to K. C. Smith and J. I. Ironstone “Eliminating interface artifact errors in bioimpedance measurements” (Smith 660); U.S. Pat. No. 7,136,697 to Michaeal G. Singer “Methods for determining illness, progression to death, and/or timing of death of biological entity” (Singer 697); U.S. Pat. No. 7,003,346 to Michaeal G. Singer, “Method for illness and disease determination and management” (Singer 346); U.S. Pat. No. 8,103,337 to M. Gravovac, J I Marteus, Z. Pavlovic and J. Ironstone “Weighted Gradient Method and System for Diagnosing Disease” (Gravovac 337); U.S. Pat. No. 6,631,292 to R. J. Liedtke, (Liedtke 292) “Bio-electrical Impedance Analyzer”; U.S. Pat. No. 8,004,291 to Naosumi Waki, “Bioelectric impedance measuring circuit”, (Waki 291); U.S. Pat. No. 7,869,866 to Giannicola Loriga; Andrea Scozzari, “Device for the monitoring of physiologic variables through measurement of body electrical impedance”, (Loriga 866); U.S. Pat. No. 7,148,701 to Sin-Chong Park; In-Duk Hwang; “Apparatus for measuring electrical impedance” (Park); U.S. Patent Application Publication No. 2010/0292603 and PCT Application Publication No. WO/2007/035887 to C. A. Shiffman, R. Aaron and S. Rutkove, “Electrical Impedance Myography” (Shiffman 887); PCT Application No. WO 2011/022068 to Seward Rutkove “A Hand-held Device for Electrical Impedance Myography” (Rutkove 068); U.S. Pat. No. 5,919,142 and PCT Application No. PCT/GB96/01499 to Boone, Kevin Graham; Holder David Simon “Electrical impedance tomography method and apparatus (Boone 142); U.S. Patent Publication No. 2005/0004490 A1 to L. W. Organ, K. C. Smith, R Safaee-Rad, M. Granvac, P. Darmos and I Gavrilov, “Electrical Impedance Method and Apparatus for Detecting and Diagnosing Diseases” (Organ 490); U.S. Patent Application Publication No. 2005/0197591 to Z. Pavlovic, M Graovuc, J. S. Ironstone, “System and Method for Prebalancing Electrical Properties to Diagnose Disease” (Pavlovic 591); U.S. Patent Application Publication No. 2004/0073131 to L. W. Organ, K. C. Smith, R Sufaee-Rad, M. Graovac, G. P. Darmos and I. Gavrilov, “Electrical Impedance Method and Apparatus for Detecting and Diagnosing Diseases” (Organ 131); U.S. Patent Application Publication No. 2004/0167422 to L. W. Organ, R Sufaee-Rad, M. Graovac, K. C. Smith, J. S. Ironstone, “Breast Electrode Array and Method of Analysis for Detecting and Diagnosing Diseases”, (Organ 422); U.S. Patent Application Publication No. 2004/0210157 L. W. Organ, K. C. Smith, R. Safaee-Rad, M. Graovac, G. P. Darmos and I. Gavrilov “Electrical Impedance Method and Apparatus for Detecting and Diagnosing Diseases” (Organ 157); U.S. Patent Application Publication No. 2004/0210158 to L. W. Organ, K. C. Smith, R. Safaee-Rad, M. Graovac, G. P. Darmos and I. Gavrilov “Electrical Impedance Method and Apparatus for Detecting and Diagnosing Diseases” (Organ 158); U.S. Patent Application Publication No. 2004/0243018 to L. W. Organ, K. C. Smith and J. S. Ironstone, “Apparatus and Method for Determining Adequacy of Electrode-So-Skin Contact and Electrode Quality for Bioelectrical measurements” (Organ 018); U.S. Patent Application Publication No. 2004/0243019 to M. Graovac and Z. Pavlovic, “Weighted Gradient Method and System for Diagnosing Disease” (Graovac 019); U.S. Patent Application Publication No. 2008/0064979 to Z. Pavlovic, M. Graovac and J. S. Ironstone, “System and Method for Prebalancing Electrical Properties to Diagnose Disease” (Pavlovic 979); U.S. Patent Application Publication No. 2008/0076889 to L. W. Organ, R. Safaee-Rad, M. Graovac, K. C. Smith, J. S. Ironstone, “Breast Electrode Array and Method of Analysis for Detecting and Diagnosing Diseases”, (Organ 889); and U.S. Patent Application Publication No. 2008/0249432 and PCT Application No. PCT/CA04/00458 A to Semlyen and M. Graovac “Diagnosis of Disease by Determination of Electrical Network Properties of a Body Part”, (Semiyen 432). All of these patents and patent applications are incorporated herein in their entirety by reference.